2014
What Does Big Data Mean for Wearable Sensor Systems?
Abstract: SummaryObjectives:The aim of this paper is to discuss how recent developments in the field of big data may potentially impact the future use of wearable sensor systems in healthcare. Methods: The article draws on the scientific literature to support the opinions presented by the IMIA Wearable Sensors in Healthcare Working Group. Results: The following is discussed: the potential for wearable sensors to generate big data; how complementary technologies, such as a smartphone, will augment the concept of a wearab…
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Cited by 52 publications
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“…(c) Efficient and informative interpretation of data generated by wearable devices. Wearable devices may generate an abundance of data, for e.g., health-related sensor signals (Redmond et al, 2014). The challenge lies in the interpretation of such data streams and connection with health outcomes, using sensor data to guide behavioral interventions and health education.…”
Section: Grand Challengesmentioning
confidence: 99%
“…(c) Efficient and informative interpretation of data generated by wearable devices. Wearable devices may generate an abundance of data, for e.g., health-related sensor signals (Redmond et al, 2014). The challenge lies in the interpretation of such data streams and connection with health outcomes, using sensor data to guide behavioral interventions and health education.…”
Section: Grand Challengesmentioning
confidence: 99%
“…Approaches for semi-automatic verification of data quality derived from ICT-based RWE procedures are the subject of active research. Specific problems of data quality for wearable sensors may, for instance, arise from poor device placement [ 75 ] and lack of a gold standard. In addition, a low signal-to-noise ratio may blur signal structure.…”
Section: Requirements For Rwe Obtained By Sensor Technologymentioning
confidence: 99%
“…There are a variety of passive monitoring projects for bipolar disorder, mostly in the pilot phase, with examples shown in Table 5 . The implementation of routine passive monitoring for large numbers of patients faces many hurdles, including patient acceptance, physician usability, and processing large volumes of data from sensors (Redmond et al 2014 ; Muench 2014 ). Many passive monitoring projects involve smartphones.…”
Section: Data Sources From Patients and Non-providersmentioning
confidence: 99%
“…Many passive monitoring projects involve smartphones. Both the differing physical characteristics of the standard devices available to consumers such as sensor accuracy and memory size, and methods selected for analysis may impact the findings (Banaee et al 2013 ; Redmond et al 2014 ). The sales of smartphones are flat in developed countries with saturation reached, and usage patterns vary among countries (Thomas 2014 , Waters 2015 ).…”
Section: Data Sources From Patients and Non-providersmentioning
confidence: 99%
